The use of glucose measurements to improve screening for diabetes in clinical practice

Authors

  • Adam R Nicholls Human Development and Health Academic Unit, University of Southampton University Hospital Southampton NHS Foundation Trust
  • Dankmar Böhning Southampton Statistical Sciences Research Institute, University of Southampton
  • Richard Holt Human Development and Health Academic Unit, University of Southampton University Hospital Southampton NHS Foundation Trust
  • Patrick Sharp University Hospital Southampton NHS Foundation Trust

DOI:

https://doi.org/10.15277/bjd.2016.090

Keywords:

type 2 diabetes, screening, prevention, HbA1c

Abstract

Introduction: It is estimated that 4 million people will be living with diabetes in England by 2025. It is imperative that we can accurately identify people at risk of diabetes and target interventions to prevent its development.

Aim: To determine whether the addition of glucose measurements to the Leicester Risk Assessment Score (LRAS) improves the prediction of HbA1c ≥42mmol/mol (6.0%) compared with a risk score alone, and reduces the number requiring additional tests to determine their glycaemic status.

Method: LRAS and HbA1c were assessed in 484 participants (aged 40–80 years). 184 participants recruited directly from primary care underwent a fasting glucose measurement while 300 participants recruited through advertisement to the general public attended for a random capillary glucose.

Results: A LRAS of ≥17 had a sensitivity of 79.6% and specificity of 60.1% to predict the HbA1c value of ≥42 mmol/mol (6.0%). The addition of a fasting glucose to the LRAS improved the explained variation in HbA1c from 20.8% with a risk score alone to 46.7%. In addition the number of people requiring further assessment of their glucose status was reduced from 43.8% to 33.2%. The addition of a random capillary glucose to the LRAS did not significantly improve the model.

Conclusions: The addition of a fasting blood glucose, but not a random capillary glucose, to the LRAS improves the prediction of HbA1c ≥42mmol/mol (6.0%) and reduced the number of people who would need further diagnostic testing for diabetes.

References

Waugh NR, Shyangdan D, Taylor-Phillips S, Suri G, Hall B. Screening for type 2 diabetes: a short report for the National Screening Committee. Health technology assessment 2013;17:1-90. http://dx.doi.org/10.3310/hta17350

International Expert Committee. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327-34. http://dx.doi.org/10.2337/dc09-9033

Chamnan P, Simmons RK, Forouhi NG, et al. Incidence of type 2 diabetes using proposed HbA1c diagnostic criteria in the european prospective investigation of cancer-norfolk cohort: implications for preventive strategies. Diabetes Care 2011;34:950-6. http://dx.doi.org/10.2337/dc09-2326

Preiss D, Khunti K, Sattar N. Combined cardiovascular and diabetes risk assessment in primary care. Diabet Med 2011;28:19-22. http://dx.doi.org/10.1111/j.1464-5491.2010.03157.x

National Institute for Health and Care Excellence (NICE). Preventing type 2 diabetes: risk identification and interventions for individuals at high risk. Public Health Guideline no 38. London 2012.

National Cardiovascular Intelligence Network. NHS Diabetes Prevention Programme (NHSDPP) Non-diabetic Hyperglycaemia. Public Health England, London, 2015.

Gillett M, Brennan A, Watson P, et al. The cost-effectiveness of testing strategies for type 2 diabetes: a modelling study. Health Technol Assess 2015;19:1-80. http://dx.doi.org/ 10.3310/hta19330

Gray LJ, Taub NA, Khunti K, et al. The Leicester Risk Assessment score for detecting undiagnosed Type 2 diabetes and impaired glucose regulation for use in a multiethnic UK setting. Diabet Med 2010;27:887-95.http://dx.doi.org/10.1111/j.1464-5491.2010.03037.x

Gray LJ, Davies MJ, Hiles S, et al. Detection of impaired glucose regulation and/or type 2 diabetes mellitus, using primary care electronic data, in a multiethnic UK community setting. Diabetologia 2012;55:959-66. http://dx.doi.org/10.1007/s00125-011-2432-x

Lindstrom J, Tuomilehto J. The diabetes risk score: a practical tool to predict type 2 diabetes risk. Diabetes Care 2003;26:725-31. http://dx.doi.org/10.2337/diacare.26.3.725

Collins GS, Altman DG. External validation of QDSCORE((R)) for predicting the 10-year risk of developing Type 2 diabetes. Diabet Med 2011; 28:599-607. http://dx.doi.org/10.1111/j.1464-5491.2011.03237.x

Gray LJ, Khunti K, Edwardson C, et al. Implementation of the automated Leicester Practice Risk Score in two diabetes prevention trials provides a high yield of people with abnormal glucose tolerance. Diabetologia 2012;55:3238-44. http://dx.doi.org/10.1007/s00125-012-2725-8

Böhning D HH, Patilea V. A limitation of the diagnostic-odds ratio in determining an optimal cut-off value for a continuous diagnostic test. Stat Methods Med Res 2011;20:541-50. http://dx.doi.org/10.1177/0962280210374532

Griffin SJ, Borch-Johnsen K, Davies MJ, et al. Effect of early intensive multifactorial therapy on 5-year cardiovascular outcomes in individuals with type 2 diabetes detected by screening (ADDITION-Europe): a cluster-randomised trial. Lancet 2011;378:156-67. http://dx.doi.org/10.1016/S0140-6736(11)60698-3

NHS England. NHS Diabetes Prevention Programme 2015. Available from: https://www.england.nhs.uk/ourwork/qual-clin-lead/action-for-diabetes/diabetes-prevention/.

The Emerging Risk Factors Collaboration. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 2010;375:2215-22. http://dx.doi.org/10.1016/S0140-6736(10)60484-9

Colagiuri S, Lee CMY, Wong TY, et al. Glycemic thresholds for diabetes-specific retinopathy: implications for diagnostic criteria for diabetes. Diabetes Care 2011;34:145-50. http://dx.doi.org/10.2337/dc10-1206

Khaw KT, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin A1c with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Ann Intern Med 2004;141:413-20. http://dx.doi.org/10.7326/0003-4819-141-6-200409210-00006

Muntner P, Wildman RP, Reynolds K, Desalvo KB, Chen J, Fonseca V. Relationship between HbA1c level and peripheral arterial disease. Diabetes Care 2005;28:1981-7. http://dx.doi.org/10.2337/diacare.28.8.1981

Hyperglycaemia in Acute Coronary Syndromes Costing Statement: Implementing NICE guidelines. In: Excellence NIfHaC, editor. London 2011.

Hu Y, Liu W, Chen Y, et al. Combined use of fasting plasma glucose and glycated hemoglobin A1c in the screening of diabetes and impaired glucose tolerance. Acta Diabetol 2010;47:231-6. http://dx.doi.org/10.1007/s00592-009-0143-2

Engelgau MM, Thompson TJ, Smith PJ, et al. Screening for diabetes mellitus in adults. The utility of random capillary blood glucose measurements. Diabetes Care 1995;18:463-6. http://dx.doi.org/10.2337/diacare.18.4.463

Simmons D, Williams DR. Random blood glucose as a screening test for diabetes in a biethnic population. Diabetic Med 1994;11:830-5. http://dx.doi.org/10.1111/j.1464-5491.1994.tb00364.x

El-Agouza I, Abu Shahla A, Sirdah M. The effect of iron deficiency anaemia on the levels of haemoglobin subtypes: possible consequences for clinical diagnosis. Clin Lab Haematol 2002;24:285-9. http://dx.doi.org/10.1046/j.1365-2257.2002.00464.x

John WG. Use of HbA1c in the diagnosis of diabetes mellitus in the UK. The implementation of World Health Organization guidance 2011. Diabetic Med 2012;29:1350-7.

Downloads

Published

2016-09-18

Issue

Section

Current Topics

Most read articles by the same author(s)